Machine Learning – Twitter Sentiment Analysis in Python
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 45M | 844 MB
Genre: eLearning | Language: English
Use Python and the Twitter API to Build Your Own Sentiment Analyzer. Sentiment Analysis, or Opinion Mining, is a field of Neuro-linguistic Programming that deals with extracting subjective information, like positive/negative, like/dislike, and emotional reactions. In this Twitter Sentiment Analysis in Python online course, you’ll learn real examples of why Sentiment Analysis is important and how to approach specific problems using Sentiment Analysis. Learn why Sentiment Analysis is useful and how to approach the problem using both Rule-Based and Machine Learning-Based approaches. The details are really important – training data and feature extraction are critical. Sentiment Lexicons provide us with lists of words in different sentiment categories that we can use for building our feature set. All this is in the run up to a serious project to perform Twitter Sentiment Analysis. We’ll spend some time on Regular Expressions which are pretty handy to know as we’ll see in our code-along. Supplemental Material included!
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